A variety of entities, including government agencies, can provide assignments (such as licenses) for segments of radio frequency spectrum. These assignments can be for specified geographic areas, for specified times, and for unlicensed, shared, and/or secondary license use. These assignments can provide relatively static prescriptions for use of spectrum resources.
Access to data representations of relatively dynamic actual usage and patterns of usage across channels, geographies (locations), and times can be advantageous in planning for resource utilization, and in structuring pricing for spectrum resources. Actual usage of spectrum resources can vary dynamically. Significant opportunities to advantageously utilize spectrum resources can be identified from relatively dynamic representations of actual usage.
Thus there is a need to provide systems and methods for providing relatively dynamic representations of actual usage of spectrum resources across channels, locations, and times. Representations of direct measurements of usage can be helpful in developing additional advantageous information, such as models and/or descriptions of patterns and trends in usage. Thus there is a need to provide systems and methods for providing such additional information.
Thus there is a need for spectrum usage sensing techniques for generating database(s) that represent spectrum usage, and for techniques to support modeling of usage and development of pricing structures.
A cognitive radio system can scan a range of spectrum by applying appropriately granular temporal sampling time intervals and thereby sense specific transmission activities in specific bands and/or channels and/or frequencies of a target spectral range. Sampling across a specific range of spectrum can be performed with a granularity that corresponds to specific communication protocols, such as protocols based on orthogonal frequency-division multiplexing (OFDM) signaling schemes. A sampling campaign can apply such sampling techniques across specified ranges of spectrum, which can include unlicensed and/or secondary license spectrum. A cognitive radio system can employ such a sampling campaign for instances of sampling times, and thereby determine measures of occupancy for specified range of spectrum. In some embodiments, a specified range of spectrum can correspond to one or more specified channels.
A cognitive radio system that can sense such specific transmission activities can comprise a Sensing Station. A Sensing Station can provide sensing capabilities for specified ranges of spectrum, for specific geographic locations. A specified geographic area comprising locations sensed by a Sensing Station can be described as a corresponding coverage area.
A database comprising measured usage for specific geographic locations can thereby be developed. Such a Spectrum Usage Database (SUD) can comprise measures of occupancy corresponding to granular sampling along dimensions of frequency (spectrum), time, and location. Such a database can be representative and/or support modeling of actual spectrum usage for coverage areas that correspond respectively to specific Sensing Stations. Such a database can also be employed to model and/or derive spectrum usage for geographic locations that correspond to relatively sparse measurements. That is, measures of occupancy can be developed by modeling etc., for locations that have few or even essentially no corresponding measurements.
Diagram 101 depicts a specified geography 102 containing Sensing Stations 112 122 132, each with a respectively corresponding coverage area 110 120 130. The area 140 is in some sense not covered by the depicted coverage areas. That is, area 140 constitutes a geographic location that corresponds to relatively sparse measurements. Thus area 140 can be a candidate for the development of measures of occupancy modeled and/or derived from spectrum usage database(s) corresponding to other coverage areas, such as those for areas 110 120 and/or 130.